Per- and Polyfluoroalkyl Substances in Southern Ontario Drinking Water and Wastewater
Bibliographic record
Abstract
The presence of 41 per- and polyfluorinated alkyl substances (PFAS) was investigated in raw and finished drinking water and in influent and effluent wastewater sampled from facilities in the Great Lakes Basin region of Southern Ontario, Canada (September–November 2023). Based on US Environmental Protection Agency Method 1633A, the method developed for analysis of these species demonstrates high sensitivity and recovery with limits of quantitation that range between 0.075 ng L –1 and 3.0 ng L –1 . Linear chain PFAS with carboxylic acid and sulfonic acid groups were detected in finished water from all drinking water treatment plants ( n = 6). Wastewater effluents ( n = 2) had PFAS concentrations approximately 1 order of magnitude higher than those in finished drinking water samples and included several fluorotelomers and ether-linked species. Across all sites, 13 of the 41 PFAS were detected in drinking water and 21 in wastewater. Average sum of 25 PFAS in finished drinking water ranged between 8.69 and 14.0 ng L –1, well below Health Canada’s objective of 30 ng L –1 . These results highlight the persistence of PFAS across treatment systems and suggest a potential feedback loop where wastewater effluents reintroduce PFAS into surface waters used as drinking water sources.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".